Unsupervised Learning in a Framework of Information Compression by Multiple Alignment, Unification and Search

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This paper describes a novel approach to unsupervised learning that has been developed within a framework of "information compression by multiple alignment, unification and search" (ICMAUS), designed to integrate learning with other AI functions such as parsing and production of language, fuzzy pattern recognition, probabilistic and exact forms of reasoning, and others.
39 pages, 1 JPEG figure

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Artificial Intelligence, Machine Learning, I.2.4; I.2.6; I.2.7

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http://salesiana.dossiersoluciones.com/handle/123456789/31462

Consulte el texto completo en el siguiente enlace:

https://arxiv.org/abs/cs/0302015
 http://arxiv.org/abs/cs/0302015

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arXiv